1. Field of the Invention
The present invention relates to the use of computer systems to facilitate the recommendation of goods or services. In one aspect, the present invention relates to a system and method for generating purchase recommendations by using historical transaction data and additional information relevant to the purchase environment as scoring criteria to determine the relative effectiveness of any recommendation and/or selling point message.
2. Description of the Related Art
Conventional computer-based approaches for providing purchase recommendations on web sites to customers have traditionally used historical transaction data to generate association rules that are used, alone or in combination of customer-input profile information, to generate one or more recommendations for consideration by the customer. When there are multiple recommendations available for customer consideration, the recommendations may be ranked using selected scoring criteria (such as margin or expected margin) to select and prioritize the candidate recommendations by multiplying the profit value and purchase probability for the recommended item. One drawback from the conventional approach of relying on customer-input profile information is that the data provided by the customer may be incomplete, or may not fully characterize the customer's profile. Also, conventional recommendation selection processes may waste a recommendation on something that is already prominent on the site and that the user has already had prior chances to buy; or may waste a recommendation on something that is already well understood and that will not benefit from further explanation; or may fail to choose a selling message that is customized for the user. In addition, conventional selection processes use a predetermined selling point message for each recommended item that is neither optimized for the customer nor taken into account in the selection process.
As seen from the conventional approaches, a need exists for methods and/or apparatuses for improving the generation and scoring of recommendations and selling point messages. There is also a need for more sophisticated identification of recommendations which focuses the presentation of recommendations to customers so that recommendations have an improved chance of being accepted by being presented in a compelling and coherent way. Further limitations and disadvantages of conventional systems will become apparent to one of skill in the art after reviewing the remainder of the present application with reference to the drawings and detailed description which follow.